People counting is becoming an important tool. People counting systems have applications in security, entertainment, retail, and other fields. Various video-based people counting systems are commercially available. Such systems have the advantage that they can determine the directions in which people are moving.
A video-based people counting system could be placed, for example, in the entrance of a retail establishment and used to detect patterns in when patrons enter and leave the retail establishment.
Historically, automated people counting systems have had the problem that there is no way to determine their accuracies in a consistent and ongoing basis. This critical flaw leads to a lack of confidence in the numbers that are produced.
Attempts have been made to come up with mechanisms for determining system accuracy in the past. These mechanisms fall into two basic categories: 1) Using humans to verify counts, either by counting live or by recording a video and counting at a later time. It has been shown that even humans well trained in the art of counting fatigue too quickly to produce accurate numbers. Additionally, the cost of verifying the performance of an automatic people counting system using human counters makes it impractical to take into account changes in environmental and traffic patterns over longer periods of time. Finally, it is very difficult to correlate the data generated by an automatic counting system with data generated by human counters, thus making it even more difficult to determine when the errors actually occurred. 2) Another possibility is to use additional automated counting systems. These types of solutions have the advantage that they are consistent and do not tire as humans do but they tend to be expensive, require additional infrastructure and introduce issues related to their own counting failures. Again, these systems have to be permanently installed in order to monitor changes in accuracy resulting from alterations to environmental parameters and traffic patterns. Finally, integrating counting data and registering failures is still a difficult if not impossible problem.
Some examples of video based people counting systems are Yakobi et al. U.S. Pat. No. 6,697,104; Guthrie U.S. Pat. No. 5,973,732; Conrad et al. U.S. Pat. No. 5,465,115; Mottier U.S. Pat. No. 4,303,851; Vin, WO 02/097713; Ming et al. EP 0 823 821 A2; and Boninsegna EP 0 847 030 A2.
There is a need for reliable and cost effective methods and systems for verifying the accuracy of systems for counting people or other movable objects.